Organized Sound Spaces with Machine Learning
Organized Sound Spaces with Machine Learning
Dr. Kıvanç Tatar
1. Materiality of Music
1.2.2 Music as Organized Sound
Music as Organized Sound – Derbyshire
Without getting too much into the details of materiality of music, the video below exemplifies how a composer works with the materiality of music in music production. The composer, Delia Derbyshire is using any sounds, processing them, and making a composition out of those sound organizations and in this video. Delia Derbyshire explains what kind of musical materials she used to compose [arrange] the theme [title music] of Doctor Who.
In the video above, Derbyshire (1965) reveals how she worked with any sounds in her compositions:
In that video, Delia Derbyshire showed us how she was selecting different kinds of audio, and how they relate to each other. For example, how does a sinusoidal sound? How does a square wave sound? After selecting the musical material, we observed how Delia Derbyshire is composing by organizing the selected material in time. Like many other composers, Delia Derbyshire (1965) organized musical material consisted of any sound, to compose [arrange] the Doctor Who theme [title music] using that material:
This documentary from BBC is a great example to see how a composer works with latent audio spaces and temporal organization of sound (figure 1). The latent audio spaces are rooted in our understanding, perception, comprehension and conceptualization of audio similarity and audio dissimilarity. It also showcased how we organize sounds in time, so that we come up with musical form. Whether it is a performance or composition, We can map both of those musical organizations to machine learning approaches. For example, to organize sounds in an abstract space of similarity and dissimilarity, we can use the notion of latent space in machine learning and use various machine learning approaches to create those latent spaces. On the other hand, to organize sounds in time, we can use a variety of sequence modeling approaches or machine learning approaches for time series data.